Lead Process Engineer - Observe to Agent Delivery

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About this role:
Wells Fargo is seeking a Lead Process Engineer within the COO AI Center of Excellence. This role focuses on applying task mining, process intelligence, and advanced observation technologies to uncover, assess, and deliver high-value process optimization and automation opportunities across large-scale enterprise initiatives. The position plays a critical role in integrating process-insight capabilities to build scalable, repeatable solutions that improve operational efficiency and business value.
In this role, you will:
Observe-to-Agent (O2A) Delivery

• Execute O2A lifecycle activities (Observe → Optimize → Analyze → Run)
• Support configuration of Observe Assistant, activity tagging, persona behavior modeling.
• Work with engineering to translate observed behavior into actionable agentic features.

Cross-Functional Delivery Leadership

• Track milestones, validate data quality, resolve blockers, and ensure timely delivery Partner with Business Sponsors, product owners, data scientists, and operations SMEs.

Workforce & Productivity Analytics Execution

• Conduct observation deployments across selected personas and applications.
• Build behavioral and task-level insights to support productivity improvement
• Run end-to-end analysis of task-level behavior, cognitive load indicators, and exception patterns.

Data Integration & Analysis

• Work with teams to enable advanced masking, clickstream, LLM-driven insights, and multi-application analysis. Support validation of call-time analytics, multitasking behavior, mainframe activity capture.

Process Intelligence Execution

• Deploy SKAN.ai agents, configure masking, validate data capture, ensure compliance with governance and privacy requirements.
• Operate and refine the SKAN Digital Twin: observe workflows, identify inefficiencies, and generate insights for optimization.
• Generate structured process documentation (SOPs) for downstream automation teams.
• Monitor continuous observation cycles and maintain audit/logging standards.

Required Qualifications:

• 5+ years of Process Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

Desired Qualifications:

• Hands-on experience with SKAN.ai or similar task/process mining tools.
• Understanding of task mining & masking configurations.
• Strong Process Design and Object Driven process modeling, including BPMN 2.0 knowledge
• Proficiency in process analytics, workflow analysis, and productivity studies.
• Ability to read and interpret system logs, user-activity capture, or desktop-analytics outputs.
• Familiarity with LLM-driven insights and continuous observation frameworks.

Job Expectations:

• This position is not eligible for Visa sponsorship.
• Ability to work on site in a hybrid role.
• Fully remote work locations are not available for this role. If you are not in a location listed on the posting, you must commit to relocation within an agreed upon timeframe.

Posting End Date:
8 Mar 2026
*Job posting may come down early due to volume of applicants.
We Value Equal Opportunity
Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.
Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit's risk appetite and all risk and compliance program requirements.
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